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» Analysis of Microarray Titration Experiments
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BMCBI
2010
214views more  BMCBI 2010»
13 years 8 months ago
AutoSOME: a clustering method for identifying gene expression modules without prior knowledge of cluster number
Background: Clustering the information content of large high-dimensional gene expression datasets has widespread application in "omics" biology. Unfortunately, the under...
Aaron M. Newman, James B. Cooper
BMCBI
2010
164views more  BMCBI 2010»
13 years 6 months ago
Merged consensus clustering to assess and improve class discovery with microarray data
Background: One of the most commonly performed tasks when analysing high throughput gene expression data is to use clustering methods to classify the data into groups. There are a...
T. Ian Simpson, J. Douglas Armstrong, Andrew P. Ja...
BIBE
2007
IEEE
153views Bioinformatics» more  BIBE 2007»
13 years 10 months ago
Combined expression data with missing values and gene interaction network analysis: a Markovian integrated approach
—DNA microarray technologies provide means for monitoring in the order of tens of thousands of gene expression levels quantitatively and simultaneously. However data generated in...
Juliette Blanchet, Matthieu Vignes
BMCBI
2010
153views more  BMCBI 2010»
13 years 7 months ago
DiffCoEx: a simple and sensitive method to find differentially coexpressed gene modules
Background: Large microarray datasets have enabled gene regulation to be studied through coexpression analysis. While numerous methods have been developed for identifying differen...
Bruno M. Tesson, Rainer Breitling, Ritsert C. Jans...
BMCBI
2004
154views more  BMCBI 2004»
13 years 8 months ago
Accuracy of cDNA microarray methods to detect small gene expression changes induced by neuregulin on breast epithelial cells
Background: cDNA microarrays are a powerful means to screen for biologically relevant gene expression changes, but are often limited by their ability to detect small changes accur...
Bin Yao, Sanjay N. Rakhade, Qunfang Li, Sharlin Ah...